In applications of satellite remote sensing and broadcasting, data compression is often necessary due to communications channel limited bandwidth. When data is compressed, the data is typically encoded with a header, such as the frame header with a sync mark. The header contains much more important information than other data segments, such as the length of the following compressed data segment. The bit error rate (BER) communications requirement of a communication system is specified based on need to accurately receive the header data whereas the nonheader data, such as trailing compressed data receives the same BER requirement. High BER requirements are wasteful when the BER requirement is strictly based on headers, as the BER requirement for the header data is too stringent for the compressed data.
As an example, a next generation of satellite systems will provide up to 140 Mbps for sensor data during downlink from satellite to a ground control center and 32 Mbps for global rebroadcasting from the ground control center back to satellite and then to smaller remote user terminals. However, the allocated bandwidths are limited for both sensor data and global rebroadcasting. The use of higher-order modulations is needed to conserve spectrum. An 8-ary phase shift keying (8PSK) modulation system sends three bits per channel symbol. A 16-ary quadrature amplitude modulation (16QAM) system sends 4 bits per channel symbol. To compensate the reduction of about 4 dB of power efficiency introduced by 8PSK and 16QAM, a forward error correction FEC code needs to be adopted. A rate ¾ convolutional code can recover this loss as taught by Charles Wang, Donald Olsen, and Roger Heymann in Widespread Satellite Communication Use and Availability Of Advanced Modulations and Forward Error Correction Coding, Proceedings of Satellite Data Compression, Communication, and Management Sub-Conference in SPIE 2005 International Symposium on Optics and Photonics, San Diego, CA, Jul. 31-Aug. 4, 2005.
The quality of the uncompressed JPEG2000 data is not acceptable after passing through a protected channel that provides a BER of 10−5 as taught by Donald Olsen et al., in the Assessment of Error Propagation in Ultraspectral Sounder Data via JPEG2000 Compression and Turbo Coding, Proceedings of Satellite Data Compression, Communication, and Management Subconference at the SPIE 2005 International Symposium on Optics and Photonics, San Diego, Calif., Jul. 31-Aug. 4, 2005. This channel protection is because the entire frame of decompressed picture data is completely corrupted when an error occurs in the header. Therefore, a stringent BER requirement for the header must be specified. For example, the required BER for headers may be set to be 10−6. An EC/NO value of 8.8 dB is required to achieve this BER when rate ¾ convolution code and 16QAM are used. Nevertheless, the data other than header definitely does not need such a stringent BER requirement.
Prior to transmission, a compressor compresses original data into the header and the compressed data. The header and compressed data may be further encoded using a convolutional encoder for providing convoluted data. The convoluted data is modulated into symbols where the coded header and coded compressed data bits are modulated into electrical signals indicating symbols. The symbols are communicated within a coded data structure defining a coded data frame. The compressed data and header are encoded into convoluted data. The convoluted data bits are grouped into M-ary symbols that are respectively mapped to points in the constellation space. The symbols are modulated into M-ary PSK or M-ary QAM electrical signals. The procedures of grouping, mapping, and modulating are conducted at the same time and considered as part of the modulation process.
An entire frame of compressed data including header is modulated within a transmission modulation method, such as quadrature amplitude modulation (QAM) where the symbols are QAM symbols. The QAM transmission method acts upon predetermined sets of data, such as four bit sets, for providing the respective communicated symbols, such an 16-ary symbols, for defining a signal constellation space having 16 predetermined points within the constellation space, such as a 16-ary QAM signal constellation space. The transmitted symbol electrical signals are received and compared to the symbol signal constellation for demodulating the received symbols into corresponding data bits or soft metrics that are used for further decoding if a FEC code is used. As such, the input data frame bits are grouped into symbols that are electrically modulated within the constellation space that may be, for example, a 16-ary QAM signal constellation space referred herein as 16QAM constellation space.
An original input data set may be compressed into an input data frame using conventional compression methods. The resulting input data frame may include a header segment and a compressed data segment grouped in an input data frame. The header and compressed data can also be then encoded where the input data is encoded using a block or convolutional encoder for providing encoded input data. The encoded input data is then modulated within a transmission modulation method, such as QAM where the symbols are QAM symbols. The encoded data is modulated into symbols where the encoded data bits are modulated into electrical signals indicating transmitted symbols. The symbols are communicated within a data structure defining a coded data frame when the input data was encoded. The QAM transmission method acts upon predetermined bit sets of the encoded input data, such as four bit sets, for providing the respective communicated symbols, such an 16-ary QAM symbols, for defining a signal constellation space having 16 predetermined points with the constellation, such as a 16QAM signal constellation.
A set of possible symbols is effectively electrically mapped into the constellation space that is used to demodulate the received symbols into respective data sets or soft metrics. The symbol electrical signals are matched to symbol points to which the electrical signals are most closely aligned for providing received data sets or soft metrics. The transmitted symbols are transmitted as electrical signals that are received and compared to the symbol signal constellation space for demodulating the received symbols into corresponding data bits or soft metrics that may be encoded output data. The received coded data sets or soft metrics indicate coded data. The coded data sets or soft metrics are decoded into output data. The decoding can be by a block decoder or a convolutional decoder operating on the received coded data sets, or a Viterbi decoder operating upon the soft metrics for providing a likelihood determination of uncoded output data. The encoded output data can be decoded using a decoder to provide output data, which may be the header and compressed data where compression is used. The output data being compressed data can then be decompressed into the original input data.
When the symbol encoded header data, or simply the header, and symbol encoded compressed data, or simply the compressed data, in an encoded data frame, are received as communicated symbols, the received symbols are decoded by a most likely mapping to the symbol points of the constellations. The header data and the compressed data are equally encoded using a block encoder or convolutional encoder into an encoded data frame providing redundancy equally across the entire input data frame. The coded bits are grouped into symbols with respective symbol points. The symbol points in the constellation space are equally spread throughout the constellation that may be a quadrature constellation signal space having M-ary points, such as 16 points in a 16QAM symbol constellation. As such, the header and the compressed data are equally encoded into symbols that equally modulated in the constellation space having equal point spacing or spreading for equal like demodulation and decoding upon reception. When both the header and compressed data have the same data-to-symbol encoding and are mapped into the same constellation space with equally spaced points in the constellation, both the header segment and the compressed data segment of the input data frame have the same BER upon reception.
Communicated frames of header and compressed data maybe subject to convolution codes that increase the number of bits of a frame. The increased number of bits is redundancy data used for improved reception. The increased number of bits providing redundancy for the communicated bits improves the BER at the expense of transmitting more bits. Hence, there is a tradeoff in bandwidth and BER. The header and compressed data is subject to the same level of redundancy defined by a code rate which is an inverse of one plus the redundancy rate. The convolution code for providing redundancy improves data recovery, and hence, improves the overall BER. The redundancy and consequential improved BER performance is equally spread across the entire frame. The use of redundancy however consumes channel bandwidth as a trade off between BER required performance and bandwidth used. As such, both convolution redundancy and symbol modulation of equally spaced points of a constellation space provide equal BER performance across an entire encoded data frame of header and compressed data.
Prior to transmission, data can be compressed into compressed data. Compressed data can be convoluted into convoluted data. Convolution produces redundancy for improved BER at a cost of increased bandwidth requirements. The convoluted data frame bit sets are encoded into symbols. The symbols are modulated, such as 16QAM, into a constellation space having predetermined equally spaced constellation points. The modulated symbols are transmitted as electrical transmitted signals over a channel, such as a Gaussian channel. Received electrical signals are compared to the constellation space for determining the most likely data sets or soft metrics, both of which indicated coded data. A stream of symbols provides a stream of bit sets or soft metrics. The bit sets or soft metrics are decoded into the original header and compressed data. The header and compressed data can be decoded into the original data. The redundancy during decoding is used to improve the reliability of the received data bits. The difference between the original data and the decoded received data indicates the BER.
In communications, it is often necessary for the header to be more reliably received with high header reliability. The higher reliability also determines the reliability of the received compressed data portion of a frame that does not necessarily require the same high level of received reliability, that is, with the same required BER performance. Improved BER performance has the disadvantage of increased bandwidth requirements. However, the higher reliability of the compressed data in the frame is not necessary as compared to the header. As such, conventional convolutional and symbol encoding unnecessarily requires more bandwidth usage than is required for a required BER that is specified in view of the header requiring the highest reliability. Conventional communications systems do not provide convolutional and symbol encoding modulation methods that allows unequal reliability across different segments of streaming communicated data frames typically including a header requiring high reception reliability and compressed data requiring low reception reliability, for optimal bandwidth utilization for a given required BER performance. These and other disadvantages are solved or reduced using the invention.